Development of robust detection/prediction algorithms for driver/rider state monitoring of fatigue/drowsiness, stress, inattention/distraction and impairing emotions.
Development of multimodal, user oriented and adaptive information, warning, actuation and handover strategies.
Integration of the developed algorithms, sensing technologies, supportive technologies (automation, V2X) and HMI algorithms/components into driver/rider state monitoring systems.
Development of personalised driver/rider behaviour profiles, considering inter-individual differences.
Design of HMI concepts, prototypes and guidelines for automated functions that take into account driver/rider state.
Instrumentation of evaluation/demonstration tools (simulators & vehicles) to evaluate the developed systems in different environments.
Adaptation of existing EuroNCAP test protocols from non-automated to automated driving modes.
Performance of targeted tests for the selection of HMI elements that optimally support each Use Case.
Evaluation of the developed systems and use cases with a wide pool of drivers/riders under simulated, controlled and real road conditions and for different driver/rider states and automation use cases/levels.
Holistic impact assessment of automation opportunities to enhance safety by supporting the impaired driver/rider, as well as of handover transitions optimisation.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688900